Chalapathi (Chala) Koneni, Sr. Data Engineering Leader @ Amazon
"Data Quality in the Age of AI: Detecting and Preventing Silent Data Corruption"
Silent data corruption is the worst kind of failure. Pipelines run clean, tests pass, dashboards look fine—but the data is wrong, and by the time your models degrade, the damage is done. Traditional validation doesn't catch this because it's not schema breaks or nulls. It's drift, logical inconsistencies, and subtle degradation that compounds across your data ecosystem.
This talk covers what actually works at scale: the anomaly detection patterns that catch corruption early, the observability strategies that surface problems before they hit models, and the governance practices that prevent propagation. We'll examine real failures from large-scale systems—what made them hard to find, how they were detected, and the frameworks built to stop recurrence. If you're running AI on data at scale, you need to solve this problem before it solves itself the expensive way.
ABOUT THE SPEAKER
Chalapathi (Chala) Koneni is a Senior Data Engineering Leader with 20+ years of experience architecting large-scale distributed data platforms and enterprise data foundations. His work focuses on building trusted data foundations that integrate data systems, quality, governance, and AI-driven validation to improve reliability in large-scale data environments. He specializes in transforming fragmented pipelines into governed, production-grade platforms supporting decision-critical analytics at scale.
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